Friday, September 14, 2007

2002 Winged robot learns to fly

How the winged robot tries to fly (and cheat the scientists)Enlarge imageHow the winged robot tries to fly (and cheat the scientists)

Learning how to fly took nature millions of years of trial and error - but a winged robot has cracked it in only a few hours, using the same evolutionary principles.

Krister Wolff and Peter Nordin of Chalmers University of Technology in Gothenburg, Sweden, built a winged robot and set about testing whether it could learn to fly by itself, without any pre-programmed data on what flapping is or how to do it.

To begin with, the robot just twitched and jerked erratically. But, gradually, it made movements that gained height. At first, it cheated - simply standing on its wing tips was one early short cut.

After three hours, however, the robot abandoned such methods in favour of a more effective flapping technique, where it rotated its wings through 90 degrees and raised them before twisting them back to the horizontal and pushing down.

"This tells us that this kind of evolution is capable of coming up with flying motion," says Peter Bentley, who works on evolutionary computing at University College London. But while the robot had worked out how best to produce lift, it was not about to take off.

"There's only so much that evolution can do," Bentley says. "This thing is never going to fly because the motors will never have the strength to do it," he says.Balsa wood wings

The robot had metre-long wings made from balsa wood and covered with a light plastic film. Small motors on the robot let it move its wings forwards or backwards, up or down or twist them in either direction.

The team attached the robot to two vertical rods, so it could slide up and down. At the start of a test, the robot was suspended by an elastic band. A movement detector measured how much lift, if any, the robot produced for any given movement.

A computer program fed the robot random instructions, at the rate of 20 per second, to test its flapping abilities. Each instruction told the robot either to do nothing or to move the wings slightly in the various directions.

Feedback from the movement detector let the program work out which sets of instructions were best at producing lift. The most successful ones were paired up and "offspring" sets of instructions were generated by swapping instructions randomly between successful pairs.

These next-generation instructions were then sent to the robot and evaluated before breeding a new generation, and the process was repeated.Related Articles